This project will develop statistical theory that is needed to estimate the sampling variability of parameter estimates in the exploratory factor analysis model, will implement the theory in a computer program to be made available to interested researchers, and will apply the method in a series of reanalyses to several data sets collected to study the structure of personality. Much of the work to be performed is technical; however, the immediate practical benefit will be inferential tools available for the first time in factor analytic research. The work fills a void that has existed for decades in the literature. With the program one will be able to evaluate a variety of hypotheses, construct interval estimates for single parameters, and confidence regions for groups of parameters. Although the proposed research has a statistical component, it was motivated by its relevance for addressing empirical measurement problems. Consequently, a second objective is to apply the new methods in reanalyses of data sets from the domain of personality measurement. A series of studies is proposed. We will systematically re-analyze several data sets generously made available by Prof. L. R. Goldberg in his investigation of the Big Five factor model of phenotypical personality characteristics. Available are data recently collected by Tellegen that also bear on the same topic. The objective of the study is to use the new statistical tools to identify robust markers of the factors underlying these data. The hope. is to achieve homogeneous and coherent subsets of variables across the samples. Because procedures used in these analyses will be based on sound statistical methodology applied in a consistent fashion, it should be possible to obtain solutions that are especially clear. This should be valuable in contributing to the understanding of the nature and composition of the Big Five.